NL2033882A - Comprehensive Evaluation Method, System and Medium for Multi-source New Energy Power Production - Google Patents
Comprehensive Evaluation Method, System and Medium for Multi-source New Energy Power Production Download PDFInfo
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Abstract
The invention belongs to the technical field of software development and discloses a comprehensive evaluation method, system and medium for multi-source new energy power prediction. Real-time data is obtained from the storage resource pool, downloaded 5 meteorological data is obtained from the meteorological service, and new energy power prediction is realized through algorithms and models. The system displays and compares the predicted manufacturer data of all access platforms, and ranks them according to different dimensions. Upload the prediction results to the unified path, filter the reported files, and finally upload and parse the files. The invention provides a multi-source new energy 10 power prediction comprehensive evaluation system, which can satisfy the requirements of multiple manufacturers and new energy stations to manage, data query and analysis, and compare the prediction results on the system. The multi-source comprehensive evaluation method for new energy power prediction provided by the invention applies the advantages of multi-meteorological sources and high-performance computing resources to improve the 15 accuracy of power prediction and meet the requirements of power grid for fine management of new energy stations.
Description
State Grid Gansu Electric Power Company, and
Gansu Tongxing Intelligent Technology Development CO., LTD. 22/110 PDNL
Comprehensive Evaluation Method, System and Medium for Multi-source New Energy Power Prediction
The invention belongs to the technical field of software development, in particular to a comprehensive evaluation method, system and medium for multi-source new energy power prediction.
Background Technology
At present, the traditional power prediction system is deployed on the field side, and the power prediction data is reported by the field side. Only one enterprise's equipment and system can be used in one electric field cycle. The service cost of switching enterprises is high and the cycle is long, so the system can only be upgraded on-site, and the service upgrade optimization cost is high and the cycle is long.
Additionally, the power prediction service level of each station is uneven. Due to the large number of manufacturers carrying out power prediction services in the market, the large number of station services, and the increasingly standardized and strict assessment standards, the technology research and development investment and service support level of power prediction by various prediction manufacturers vary greatly, and the market is chaotic.
Due to the uneven prediction level of various service providers, the accuracy of power prediction is not high, which increases the difficulty of power grid dispatch and cannot meet the requirements of power grid for fine management of new energy stations.
The data is scattered and the linkage is not strong. At present, the power prediction transmits data from multiple points of the new energy field station to the control center, and the data is scattered. Due to the stability of the channel on the source side of the network, the system barrier and the inconsistency of the standard specification at the field end, the linkage between the data is weak.
Through the above analysis, the problems and defects of the existing technology are as follows: (1) Traditional power prediction system switching enterprises have high service cost and long cycle, so the system can only be upgraded on-site, and service upgrade optimization has high cost and long cycle.
(2) Due to the uneven prediction level of various service providers, the accuracy of power prediction is not high, which increases the difficulty of power grid dispatch and cannot meet the requirements of power grid for fine management of new energy stations. (3) At the present stage, the power prediction data is scattered, and the channel stability of the source side of the network, the system barrier and the standard specification of the field end are not unified, resulting in the weak linkage between the data.
In view of the problems existing in the prior art, the invention provides a comprehensive evaluation method, system and medium for multi-source new energy power prediction.
The invention is realized as follows: a comprehensive evaluation method oriented to multi-source new energy power prediction. The comprehensive evaluation method oriented to multi-source new energy power prediction includes: obtaining real-time data from storage resource pool, obtaining downloaded meteorological data from meteorological service, and realizing new energy power prediction through algorithm and model; The system displays and compares the predicted manufacturer data of all access platforms, and ranks them according to different dimensions. Upload the prediction results to the unified path, filter the reported files, and finally upload and parse the files.
Further, the comprehensive evaluation method for multi-source new energy power prediction includes the following steps:
Step 1: Prediction: Obtaining meteorological data (the meteorological data is mainly forecast meteorological data, and the new small-scale forecast data is obtained by downscaling the original large-scale meteorological forecast data) and storing the meteorological data to the corresponding server. Then the meteorological data are used to achieve short-term prediction and ultra-short-term prediction through different algorithms and models. The short term includes the power forecast for the next 10 days, the time granularity of the forecast data is 15min, and the forecast period is daily. Ultra-short-term forecast data are rolling forecast every 15 minutes, and the forecast time interval is 16 points in total in the next 4 hours, with a time granularity of 15min. After the prediction is completed, the corresponding prediction point data is stored. If the accuracy of the corresponding prediction is defective, the accuracy of the data is corrected by dynamically adjusting the corresponding algorithm model in real time.
Step 2: Comparison: The prediction manufacturers complete their own power prediction data and upload the corresponding power prediction data to the comparison platform through the interface or file. After receiving the corresponding data, the platform will uniformly process the data of each manufacturer, mark the corresponding manufacturer label, and display and compare the data of all the prediction manufacturers through the platform display page.
Step 3: Report: After unified processing of the obtained prediction results of each forecast manufacturer, the platform displays all forecast manufacturers with normal data.
The report files are screened by users, and then uploaded and analyzed for storage.
Furthermore, in Step 1, each power prediction manufacturer deplores power prediction service and weather download service on the platform, and obtains real-time data from the storage resource pool of the big data platform respectively. Obtain the downloaded meteorological data from the meteorological service, integrate the forecast result data according to the file format required by the provincial survey through algorithm and model calculation, and send it to the unified reporting directory; Among them, real-time data obtained from the storage resource pool of the big data platform include active power, wind speed and irradiance data.
Furthermore, in Step 2, the system displays and compares the power prediction results, power grid assessment results, accuracy rate, reporting rate and order situation data of all the prediction manufacturers connected to the platform through the unified interface, and ranks them in different dimensions to achieve the unified comparison and evaluation of the prediction results of different power prediction manufacturers. The system provides wind power and photovoltaic classification comparison, shows the comparison of short-term and ultra-short-term accuracy of different models for all power stations under each type, and compares the gap between the predicted curve and the measured curve; According to the power prediction comparison of each forecast in the system, the new energy station selects and purchases power prediction service providers on the operation platform.
Furthermore, in Step 3, each power prediction manufacturer transmits the prediction result to the specified unified path through sftp. According to the manually entered order, the system filters the report file; Upload to Region Il of provincial investigation in a unified manner through 102 protocol for warehousing analysis.
Furthermore, the forecast results include short-term, ultra-short-term, inverter and weather station files.
Another purpose of the invention is to provide a comprehensive evaluation system for multi-source new energy power prediction by applying the comprehensive evaluation method for multi-source new energy power prediction. The comprehensive evaluation system for multi-source new energy power prediction comprises:
Prediction module, which is used to obtain real-time meteorological data and realize power prediction through algorithm and model;
Comparison module, which is used to display and compare the data of all the prediction manufacturers connected to the platform;
Report module, which is used to obtain prediction results, filter report files, and then enter the database for analysis.
Another purpose of the invention is to provide a computer device, which comprises a memory and a processor, and the memory stores a computer program, which, when executed by the processor, enables the processor to perform the steps of the comprehensive evaluation method for multi-source new energy power prediction.
Another purpose of the present invention is to provide a computer readable storage medium containing a computer program which, when executed by the processor, enables the processor to perform the steps of the comprehensive evaluation method for power prediction of multi-source new energy sources.
Another purpose of the invention is to provide an information data processing terminal, which is used to realize the comprehensive evaluation system for multi-source new energy power prediction.
Combined with the above technical scheme and the technical problem solved, the advantages and positive effects of the technical scheme to be protected by the invention are as follows:
The comprehensive evaluation method for multi-source new energy power prediction of the invention provides an innovative centralized prediction mode, so that as long as the prediction manufacturer pays attention to the prediction algorithm, the platform manufacturer mainly pays attention to the system maintenance, so that unified use and unified management can be realized only by maintaining a set of systems. Realize the comparative display of all power prediction data and indicators, multi-dimensional comparative analysis of power prediction data, centralized management of power prediction manufacturers, and in-depth mining of power prediction data. The invention can also adapt to the needs of business and technological development in the next few years. At the same time, the maturity of products and technologies should be taken into account as much as possible to ensure the overall stability of the basic platform.
The comprehensive evaluation system for multi-source new energy power prediction provided by the invention adopts the micro-service software design mode, and each module in the system is a micro-service that can be independently separated and deployed.
Combined with the Docker container technology and container cloud platform used at the bottom, the continuous integration and continuous deployment technology based on the container cloud platform can realize the rapid iterative development of the system. The system can be upgraded several to dozens of times a day to ensure the rapid and stable online of new services.
The power prediction service and meteorological download service are deployed on the platform of each power prediction manufacturer of the invention, and real-time data (active 5 power, wind speed, irradiation, etc.) are obtained from the storage resource pool of the big data platform respectively, and downloaded meteorological data are obtained from the meteorological service. Through the calculation of algorithms and models, the predicted result data are integrated in accordance with the required file format. And send it to the unified reporting directory.
The invention displays and compares the power prediction results, power grid assessment results, accuracy rate, reporting rate, order situation and other data of all the prediction manufacturers connected to the platform through a unified interface, and ranks them in different dimensions, so as to realize the unified comparison and evaluation of the prediction results of different power prediction manufacturers. The classification comparison of wind power and photovoltaic is also provided to show the comparison of short-term and ultra-short-term accuracy of different models for all power stations under each type, and to visually compare the gap between the predicted curve and the measured curve.
The invention improves the accuracy of prediction. Simple and centralized deployment allows forecasting vendors to devote more human and material resources to the key goal of improving forecast accuracy. There is no need to worry about the quality of measured data affecting the accuracy of prediction, no need to worry about the complex network from the electric field to the power grid affecting the timely reporting of prediction data, no need to spend time and energy to the electric field site to deal with a simple or complex problem, no need to worry about the hardware limitations affecting the complex calculation of data.
The invention reduces the number of interfaces between the power grid system and the
Internet and improves the network security of the power grid system. Based on the current centralized monitoring system of the power grid to obtain real-time data of the electric field, and an external network outlet of the power grid to obtain meteorological data of all stations, the corresponding prediction function can be realized. By controlling the destination address, port, protocol and other strategies of the external network outlet at the power grid end, coupled with logical and physical isolation, the invention ensures the security and control of the Internet outlet of the power grid, which is sufficient to ensure the security of the entire power grid network.
The invention provides a multi-source new energy power prediction comprehensive evaluation system, which can satisfy the requirements of multiple manufacturers and new energy stations to manage, data query and analysis, and compare the prediction results on the system. The multi-source comprehensive evaluation method of new energy power prediction applies the advantages of multi-meteorological sources and high-performance computing resources to improve the accuracy of power prediction and meet the requirements of power grid for fine management of new energy stations.
The expected benefits and commercial value of the technical scheme of the invention after transformation are as follows: for new energy power generation enterprises, it can save a large amount of hardware, software, network and other costs required by the procurement of forecasting system. This can save the workload of the station personnel on duty to maintain each system. For the prediction manufacturer, it can save the labor cost and time cost that must go to the site to deploy and maintain the prediction system. For the power grid, the platform should be provided for the use of forecasting manufacturers and electric field owners, and reasonable service fees should be charged from it, so as to continuously promote the upgrading and improvement of centralized forecasting and provide more perfect forecasting services.
Additionally, the invention has the following advantages: 1. Portal integration
There are multiple services provided by multiple manufacturers in the power prediction application service ecosystem. A unified directory is used to display multiple power prediction services. 2. Common platform architecture
Without much hardware and software dependence, virtual machines and containerization enable secure, reliable, fast response, elastic scaling of computing resources and one-click deployment. 3. Other advantages (1) Innovative centralized prediction mode, benefiting the electric field, prediction manufacturers, power grid and other parties, and improving the accuracy of the overall new energy prediction. (2) Prediction manufacturers mainly focus on prediction algorithms, while platform manufacturers mainly focus on system maintenance. This can realize that we only need to maintain a set of systems, can achieve unified use, unified management. This avoids the decentralized deployment and maintenance of the traditional prediction system, and there will be many network hidden dangers in each electric field, which has obvious management benefits.
In order to more clearly explain the technical scheme of the implementation methods of the invention, a brief introduction will be made to the attached drawings required in the implementation methods of the invention in the following. Obviously, the attached drawings described below are only some implementation methods of the invention. For ordinary technicians in the art, other attached drawings can be obtained according to these attached drawings without paying creative labor.
Figure 1 is the flow chart of the comprehensive evaluation method for multi-source new energy power prediction provided by the implementation method of the invention.
Specific Implementation Methods
In order to make the purpose, technical scheme and advantages of the invention more clearly, the invention is further explained in the following implementation methods. It should be understood that the specific implementation method described herein are intended only to explain the invention and are not intended to qualify it.
In view of the problems existing in the prior art, the invention provides a comprehensive evaluation method, system and medium for multi-source new energy power prediction. The following is a detailed description of the invention combined with the attached figure.
In order to enable those skilled in the art to fully understand how the invention is implemented, this part is an explanatory illustrative implementation method of the technical scheme of the claim.
As shown in Figure 1, the comprehensive evaluation method for multi-source new energy power prediction provided by the implementation method of the invention comprises the following steps:
S101. Prediction: Obtain real-time meteorological data and realize power prediction through algorithms and models;
S102. Comparison: Display and comparison of the data of all the prediction manufacturers connected to the platform;
S103. Report: Obtain the prediction results and filter the report files, and then carry out warehousing analysis.
The comprehensive evaluation system for multi-source new energy power prediction provided by the implementation method of the invention comprises: 1. Business architecture implementation
Using the micro-service software design mode, each module in the system is a micro- service that can be independently separated and deployed. Combined with the Docker container technology and container cloud platform used at the bottom, the continuous integration and continuous deployment technology on the container cloud platform can realize the rapid iterative development of the system, and the system can be upgraded several to dozens of times a day. Ensure the rapid and stable launch of new business. 2. System architecture implementation
It is divided into three corresponding services: (1) Prediction function
Each power prediction manufacturer deploys power prediction service and meteorological download service on the platform, and obtains real-time data (active power, wind speed, irradiance and other data) from the storage resource pool of the big data platform respectively.
Obtain the downloaded meteorological data from the meteorological service, integrate the forecast result data according to the file format required by the provincial survey and send it to the unified reporting directory through the calculation of algorithm and model. (2) Comparison function
The system displays and compares the power prediction results, power grid assessment results, accuracy rate, reporting rate and order situation of all forecast manufacturers connected to the platform through a unified interface, and ranks them in different dimensions. This can realize the unified comparison and evaluation of the prediction results of different power prediction manufacturers. The system provides classification comparison of wind power and photovoltaic, shows the comparison of short-term and ultra- short-term accuracy of different models for all power stations under each type, and visually compares the gap between the predicted curve and the measured curve. The new energy station can choose its own power prediction service provider on the operation platform according to the power prediction comparison of each forecast in the system. (3) Reporting function
Each power prediction manufacturer will send the prediction results (short-term, ultra- short-term, inverter, weather station and other files) to the specified unified path through sftp.
The system filters the report documents according to the manually entered order. Upload to
Region Il of provincial investigation in a unified manner through 102 protocol for warehousing analysis.
The comprehensive evaluation system for multi-source new energy power prediction provided by the implementation method of the invention comprises:
Prediction module, which is used to obtain real-time meteorological data and realize power prediction through algorithm and model;
Comparison module, which is used to display and compare the data of all the prediction manufacturers connected to the platform;
Report module, which is used to obtain prediction results, filter report files, and then enter the database for analysis.
On the application server provided on site, the relevant applications are deployed in the way of micro-services, and the implementation of the scheme is completed in accordance with the three steps of prediction, comparison and reporting. In the prediction module, the connected prediction manufacturer obtains real-time and historical meteorological data, as well as historical actual power data through the platform, predicts the corresponding short- term and ultra-short-term data according to the algorithm model, and calculates whether the accuracy meets the requirements by comparing with the actual data. If the deviation is large, the data is corrected by constantly adjusting the algorithm model. The corresponding prediction accuracy requirements have been met.
The platform will display and compare the power prediction results, power grid assessment results, accuracy and reporting rates of all the connected prediction manufacturers, and rank them in different dimensions. So as to realize the unified comparison and evaluation of the prediction results of different power prediction manufacturers. The platform also provides classification comparison of wind power and photovoltaic, showing the comparison of short-term and ultra-short-term accuracy of different models for all power stations under each type, and intuitively comparing the gap between the predicted curve and the measured curve. According to the above data display, the new energy station can purchase its own power prediction service provider from the platform.
Each power prediction manufacturer in the reporting module will send the prediction results (short-term, ultra-short-term, inverter, weather station and other files) to the specified path through sftp. The user enters the order through the system and filters the corresponding report file. It is uploaded to Region II of provincial investigation through 102 protocol for warehousing analysis.
It should be noted that the implementation methods of the present invention can be realized by hardware, software or a combination of software and hardware. The hardware part can be implemented by special logic; The software component can be stored in memory and executed by an appropriate instruction execution system, such as a microprocessor or specially designed hardware. A person of ordinary skill in the art can understand that the above devices and methods can be implemented using computer executable instructions and/or included in the processor control code, For example, such code is provided on carrier media such as disks, CD, or DVD-ROM, programmable memory such as read-only memory (firmware), or data carriers such as optical or electronic signal carriers. The devices of the present invention and their modules may be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors. It can also be implemented by a combination of the above hardware circuits and software such as firmware.
The above is only the specific implementation of the invention, but the protection scope of the invention is not limited to this. Any modification, equivalent replacement and improvement made by any skilled person familiar with the technical field within the technical scope disclosed by the invention and within the spirit and principle of the invention shall be covered within the scope of protection of the invention.
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Publication number | Priority date | Publication date | Assignee | Title |
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CN109639880A (en) * | 2018-11-08 | 2019-04-16 | 维沃移动通信有限公司 | A kind of display method of weather information and terminal device |
US20190372345A1 (en) * | 2017-02-13 | 2019-12-05 | Griddy Holdings Llc | Methods and systems for an automated utility marketplace platform |
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US20190372345A1 (en) * | 2017-02-13 | 2019-12-05 | Griddy Holdings Llc | Methods and systems for an automated utility marketplace platform |
CN109639880A (en) * | 2018-11-08 | 2019-04-16 | 维沃移动通信有限公司 | A kind of display method of weather information and terminal device |
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Title |
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QIANG FAN ET AL: "Research on management system and technical standard system of wind power prediciton", 2017 IEEE 2ND ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC), IEEE, 25 March 2017 (2017-03-25), pages 873 - 879, XP033158649, DOI: 10.1109/IAEAC.2017.8054139 * |
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